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of Systems and Control, we develop both theory and concrete tools to design systems that learn, reason, and act in the real world based on a seamless combination of data, mathematical models, and algorithms
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for validation of CFD results. Implement novel unsteady CFD and next generation in-house AI based design tools validated by the gathered experimental data on GKN resources with tight collaboration
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research and modelling approaches, and in close collaboration with relevant stakeholders.Achieving our vision is based on creative collaborations within the framework of a good and equal working environment
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cancer. The goal will be to find genetic prediction models to be able to predict which childhood cancer patients have a high or low risk of toxicity in childhood cancer. Preliminary the doctoral project
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) analysing the effects of different trade-offs between timber production and biodiversity under the influence of climate change, and 3) developing optimisation models based on heuristic and AI-based methods
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introduces new and underexplored vulnerabilities to network-based threats. The goal of this research is to uncover such threats, evaluate their impact on training performance and model integrity, and develop
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CST Microwave Studio, HFSS or EM Pro for antenna modeling and design is required, as is experience with programming languages like MATLAB, Python, or similar for antenna array analysis and algorithm
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. -Machine learning code generation for autonomous translation of payload data semantics. -Dictionary learning and algorithms for translation between major data modeling languages. -Model-based System
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to investigate flow-induced forces in hydraulic turbines under varying operational conditions and how these forces affect the degradation and lifetime of the machines. About the position The position is based
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/thesis: Industry-/collaboration PhD student in optimized off-road driving in forests Research subject: Soil science Description: We are looking for an industry/collaboration-based PhD student to develop a